6 datasets found
  1. World Population Dataset

    • kaggle.com
    Updated Sep 2, 2022
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    Amit Kumar Sahu (2022). World Population Dataset [Dataset]. https://www.kaggle.com/datasets/asahu40/world-population-dataset
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Sep 2, 2022
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Amit Kumar Sahu
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Area covered
    World
    Description

    This is a Dataset of the World Population Consisting of Each and Every Country. I have attempted to analyze the same data to bring some insights out of it. The dataset consists of 234 rows and 17 columns. I will analyze the same data and bring the below pieces of information regarding the same.

    1. Continent Population Characteristics Analysis.
    2. Analysis of Countries.
      • Top 10 Most Populated and Least Populated Countries
      • Top 10 Largest and Smallest Countries as per Area
      • Population Growth From 1970 to 2020 (50 Years)
    3. Countries Represent % Of World Population.
      • Countries that represent below 0.1% of the World Population.
      • Countries that represent above 2% of the world Population
      • Top 10 Over Populated Countries based on Density Per Sq KM.
      • Top 10 Least Populated Countries based on Density Per Sq KM.
  2. World Population Statistics - 2023

    • kaggle.com
    Updated Jan 9, 2024
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    Bhavik Jikadara (2024). World Population Statistics - 2023 [Dataset]. https://www.kaggle.com/datasets/bhavikjikadara/world-population-statistics-2023
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 9, 2024
    Dataset provided by
    Kagglehttp://kaggle.com/
    Authors
    Bhavik Jikadara
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    World
    Description
    • The current US Census Bureau world population estimate in June 2019 shows that the current global population is 7,577,130,400 people on Earth, which far exceeds the world population of 7.2 billion in 2015. Our estimate based on UN data shows the world's population surpassing 7.7 billion.
    • China is the most populous country in the world with a population exceeding 1.4 billion. It is one of just two countries with a population of more than 1 billion, with India being the second. As of 2018, India has a population of over 1.355 billion people, and its population growth is expected to continue through at least 2050. By the year 2030, India is expected to become the most populous country in the world. This is because India’s population will grow, while China is projected to see a loss in population.
    • The following 11 countries that are the most populous in the world each have populations exceeding 100 million. These include the United States, Indonesia, Brazil, Pakistan, Nigeria, Bangladesh, Russia, Mexico, Japan, Ethiopia, and the Philippines. Of these nations, all are expected to continue to grow except Russia and Japan, which will see their populations drop by 2030 before falling again significantly by 2050.
    • Many other nations have populations of at least one million, while there are also countries that have just thousands. The smallest population in the world can be found in Vatican City, where only 801 people reside.
    • In 2018, the world’s population growth rate was 1.12%. Every five years since the 1970s, the population growth rate has continued to fall. The world’s population is expected to continue to grow larger but at a much slower pace. By 2030, the population will exceed 8 billion. In 2040, this number will grow to more than 9 billion. In 2055, the number will rise to over 10 billion, and another billion people won’t be added until near the end of the century. The current annual population growth estimates from the United Nations are in the millions - estimating that over 80 million new lives are added yearly.
    • This population growth will be significantly impacted by nine specific countries which are situated to contribute to the population growth more quickly than other nations. These nations include the Democratic Republic of the Congo, Ethiopia, India, Indonesia, Nigeria, Pakistan, Uganda, the United Republic of Tanzania, and the United States of America. Particularly of interest, India is on track to overtake China's position as the most populous country by 2030. Additionally, multiple nations within Africa are expected to double their populations before fertility rates begin to slow entirely.

    Content

    • In this Dataset, we have Historical Population data for every Country/Territory in the world by different parameters like Area Size of the Country/Territory, Name of the Continent, Name of the Capital, Density, Population Growth Rate, Ranking based on Population, World Population Percentage, etc. >Dataset Glossary (Column-Wise):
    • Rank: Rank by Population.
    • CCA3: 3 Digit Country/Territories Code.
    • Country/Territories: Name of the Country/Territories.
    • Capital: Name of the Capital.
    • Continent: Name of the Continent.
    • 2022 Population: Population of the Country/Territories in the year 2022.
    • 2020 Population: Population of the Country/Territories in the year 2020.
    • 2015 Population: Population of the Country/Territories in the year 2015.
    • 2010 Population: Population of the Country/Territories in the year 2010.
    • 2000 Population: Population of the Country/Territories in the year 2000.
    • 1990 Population: Population of the Country/Territories in the year 1990.
    • 1980 Population: Population of the Country/Territories in the year 1980.
    • 1970 Population: Population of the Country/Territories in the year 1970.
    • Area (km²): Area size of the Country/Territories in square kilometers.
    • Density (per km²): Population Density per square kilometer.
    • Growth Rate: Population Growth Rate by Country/Territories.
    • World Population Percentage: The population percentage by each Country/Territories.
  3. Global Digital Activism Data Set, 2013 - Version 1

    • search.gesis.org
    Updated Jun 11, 2013
    + more versions
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    ICPSR - Interuniversity Consortium for Political and Social Research (2013). Global Digital Activism Data Set, 2013 - Version 1 [Dataset]. http://doi.org/10.3886/ICPSR34625.v1
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    Dataset updated
    Jun 11, 2013
    Dataset provided by
    Inter-university Consortium for Political and Social Researchhttps://www.icpsr.umich.edu/web/pages/
    GESIS search
    License

    https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de458347https://search.gesis.org/research_data/datasearch-httpwww-da-ra-deoaip--oaioai-da-ra-de458347

    Description

    Abstract (en): The Global Digital Activism Data Set (GDADS), released February 2013 by the Digital Activism Research Project (DARP) at the University of Washington in Seattle, features coded cases of online digital activism from 151 countries and dependent territories. Several features from each case of digital activism were documented, including the year that online action commenced, the country of origin of the initiator(s), the geographic scope of their campaign, and whether the action was online only, or also featured offline activities. Researchers were interested in the number and types of software applications that were used by digital activists. Specifically, information was collected on whether software applications were used to circumvent censorship or evade government surveillance, to transfer money or resources, to aid in co-creation by a collaborative group, or for purposes of networking, mobilization, information sharing, or technical violence (destructive/disruptive hacking). The collection illustrates the overall focus of each case of digital activism by defining the cause advanced or defended by the action, the initiator's diagnosis of the problem and its perceived origin, the identification of the targeted audience that the campaign sought to mobilize, as well as the target whose actions the initiators aimed to influence. Finally, each case of digital activism was evaluated in terms of its success or failure in achieving the initiator's objectives, and whether any other positive outcomes were apparent. Through GDADS and associated works, DARP aims to study the effect of digital technology on civic engagement, nonviolent protest, and political change around the world. The GDADS contains three sets of data: (1) Coded Cases, (2) Case Sources, and (3) Coded Cases 2.0. The Coded Cases dataset contains 1179 coded cases of digital activism from 1982 through 2012. The Case Sources dataset is an original deposited Excel document that contains source listings from all cases documented by researchers, including those that were ultimately excluded from the original Coded Cases dataset. Coded Cases 2.0 contains 426 additional cases from 2010 through 2012; these cases were treated with a revised coding scheme and an extended review process. GDADS was assembled with the following inclusion criteria: cases needed to exhibit either (1) an activism campaign with at least one digital tactic, or (2) an instance of online discourse aimed at achieving social or political change, and (3) needed to be described by a reliable third party source. In addition to these inclusion criteria, researchers required that the digital activism be initiated by a traditional civil society organization, such as a nongovernmental organization or a nonprofit, or by the collaborative effort of one or more citizens. Digital activism cases initiated by governments or for-profit entities were not included in the collection. The data were assembled by a team of volunteers searching Web sites that are known to document global digital activism; researchers also collected data from peer reviewed journal articles that included digital activism case studies. This data collection does not feature a weighting scheme. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Checked for undocumented or out-of-range codes.. Global occurrences of online digital activism and journal article case studies of digital activism from 1982 through 2012. Smallest Geographic Unit: country Dataset 1: Coded Cases, contains the entire collection of coded cases, according to the inclusion criteria, for 1982-2009, but is incomplete for 2010-2012. Dataset 2: Case Sources, is an original deposited Excel document that contains links and citations used to code dataset 1 cases, plus 166 cases collected but not included in dataset 1. Dataset 3: Coded Cases 2.0, contains additional cases using purposive, multi-source, multilingual, sampling. For more information on sampling, please refer to the Methodology section in the ICPSR Codebooks. 2014-06-12 The collection has been updated with file set 3, Coded Cases 2.0, which contains additional cases that use an updat...

  4. The global gender gap index 2025

    • statista.com
    Updated Jul 2, 2025
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    Statista (2025). The global gender gap index 2025 [Dataset]. https://www.statista.com/statistics/244387/the-global-gender-gap-index/
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    Dataset updated
    Jul 2, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2025
    Area covered
    Worldwide
    Description

    The global gender gap index benchmarks national gender gaps on economic, political, education, and health-based criteria. In 2025, the country offering the most gender equal conditions was Iceland, with a score of 0.93. Overall, the Nordic countries make up 3 of the 5 most gender equal countries worldwide. The Nordic countries are known for their high levels of gender equality, including high female employment rates and evenly divided parental leave. Sudan is the second-least gender equal country Pakistan is found on the other end of the scale, ranked as the least gender equal country in the world. Conditions for civilians in the North African country have worsened significantly after a civil war broke out in April 2023. Especially girls and women are suffering and have become victims of sexual violence. Moreover, nearly 9 million people are estimated to be at acute risk of famine. The Middle East and North Africa have the largest gender gap Looking at the different world regions, the Middle East and North Africa have the largest gender gap as of 2023, just ahead of South Asia. Moreover, it is estimated that it will take another 152 years before the gender gap in the Middle East and North Africa is closed. On the other hand, Europe has the lowest gender gap in the world.

  5. H

    Replication Data for: Political Land Corruption: Evidence from Malta - the...

    • dataverse.harvard.edu
    Updated Jan 3, 2018
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    Paul Caruana-Galizia; Matthew Caruana-Galizia (2018). Replication Data for: Political Land Corruption: Evidence from Malta - the European Union's Smallest member State [Dataset]. http://doi.org/10.7910/DVN/TFINUR
    Explore at:
    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Jan 3, 2018
    Dataset provided by
    Harvard Dataverse
    Authors
    Paul Caruana-Galizia; Matthew Caruana-Galizia
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Area covered
    Europe, Malta, European Union
    Description

    Political corruption in the land sector is pervasive, but difficult to document and effectively prosecute. This paper provides new evidence on political land corruption in Malta, the European Union’s smallest member state and one of the world’s most densely populated countries. It shows how the country’s highly restrictive zoning laws, along with a de jure independent regulator, have created opportunities for extensive and endemic corruption in the granting of land development permits in zones that are outside development. It provides an example of governments creating institutions as rent-collection instruments – not to correct market failures, but to create opportunities for corruption. The unique underlying dataset was collected through an automated Web-scraping program as the regulator first turned down then ignored freedom of information requests for the data.

  6. T

    GDP by Country in AFRICA

    • tradingeconomics.com
    csv, excel, json, xml
    Updated May 27, 2017
    + more versions
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    TRADING ECONOMICS (2017). GDP by Country in AFRICA [Dataset]. https://tradingeconomics.com/country-list/gdp?continent=africa
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    xml, json, csv, excelAvailable download formats
    Dataset updated
    May 27, 2017
    Dataset authored and provided by
    TRADING ECONOMICS
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    2025
    Area covered
    Africa
    Description

    This dataset provides values for GDP reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

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Amit Kumar Sahu (2022). World Population Dataset [Dataset]. https://www.kaggle.com/datasets/asahu40/world-population-dataset
Organization logo

World Population Dataset

Country and Continent Wise World Population Dataset

Explore at:
CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
Dataset updated
Sep 2, 2022
Dataset provided by
Kagglehttp://kaggle.com/
Authors
Amit Kumar Sahu
License

https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

Area covered
World
Description

This is a Dataset of the World Population Consisting of Each and Every Country. I have attempted to analyze the same data to bring some insights out of it. The dataset consists of 234 rows and 17 columns. I will analyze the same data and bring the below pieces of information regarding the same.

  1. Continent Population Characteristics Analysis.
  2. Analysis of Countries.
    • Top 10 Most Populated and Least Populated Countries
    • Top 10 Largest and Smallest Countries as per Area
    • Population Growth From 1970 to 2020 (50 Years)
  3. Countries Represent % Of World Population.
    • Countries that represent below 0.1% of the World Population.
    • Countries that represent above 2% of the world Population
    • Top 10 Over Populated Countries based on Density Per Sq KM.
    • Top 10 Least Populated Countries based on Density Per Sq KM.
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